The dataset viewer is not available for this split.
Error code: StreamingRowsError Exception: KeyError Message: 'jpg' Traceback: Traceback (most recent call last): File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 322, in compute compute_first_rows_from_parquet_response( File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 88, in compute_first_rows_from_parquet_response rows_index = indexer.get_rows_index( File "/src/libs/libcommon/src/libcommon/parquet_utils.py", line 640, in get_rows_index return RowsIndex( File "/src/libs/libcommon/src/libcommon/parquet_utils.py", line 521, in __init__ self.parquet_index = self._init_parquet_index( File "/src/libs/libcommon/src/libcommon/parquet_utils.py", line 538, in _init_parquet_index response = get_previous_step_or_raise( File "/src/libs/libcommon/src/libcommon/simple_cache.py", line 591, in get_previous_step_or_raise raise CachedArtifactError( libcommon.simple_cache.CachedArtifactError: The previous step failed. During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/src/services/worker/src/worker/utils.py", line 96, in get_rows_or_raise return get_rows( File "/src/libs/libcommon/src/libcommon/utils.py", line 197, in decorator return func(*args, **kwargs) File "/src/services/worker/src/worker/utils.py", line 73, in get_rows rows_plus_one = list(itertools.islice(ds, rows_max_number + 1)) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1389, in __iter__ for key, example in ex_iterable: File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 234, in __iter__ yield from self.generate_examples_fn(**self.kwargs) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 126, in _generate_examples example[field_name] = {"path": example["__key__"] + "." + field_name, "bytes": example[field_name]} KeyError: 'jpg'
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Data
This datset is uploaded as a .tar.gz file that was orginally used to finetune a stable diffusion model. It consists of 11 Renaissance era portraits of human figures whom are often rendered in dynamic poses, showing expression amd possibly using gesture. Renaissance portraits are characterized by realism, with the subject being the focus of the work and the background being plain. Additionally, the file includes a .csv file with two columns, one that serves as a placeholder for an image path and the other for textual description used in training the model.
Image Format: .jpg
Image Size: 256 x 256px
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